Robust Motion Watermarking based on Multiresolution Analysis
Robust Motion Watermarking based on Multiresolution Analysis. Tae-hoon Kim Jehee Lee Sung Yong Shin Korea Advanced Institute of Science and Technology. Introduction. Watermarking Embedding signature into the media data Applications of watermarking
Robust Motion Watermarking based on Multiresolution Analysis
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Presentation Transcript
Robust Motion Watermarkingbased onMultiresolution Analysis Tae-hoon Kim Jehee Lee Sung Yong Shin Korea Advanced Institute of Science and Technology
Introduction • Watermarking • Embedding signature into the media data • Applications of watermarking • Ownership protection (robust watermarking ) • Data authentication • Fingerprinting • Secret data hiding ………
Objectives • Robust watermarking for motion data • Imperceptible • Non-invertible • Robust to attacks • smoothing, cropping, scaling, type conversion, quantization, adding noise, adding another watermark, …
registered suspect motion suspect motion Ownership Protection with Watermark insertion + watermarked motion original motion watermark analysis of similarity - extraction extracted watermark registration
Previous Work • [Schyndel et al. 1994] • Modifying the least significant bits • [Tanaka et al. 1990] • Embedding noise-like watermarks • [Cox et al. 1997] • Introducing spread-spectrum for images • [Praun et al. 1999] • Employing spread-spectrum for 3D meshes
insertion insertion + + watermarked signal watermarked signal original signal original signal watermark signal watermark signal Spread Spectrum Watermarking • Embedding a watermark with redundancy Properties of spread spectrum: JR (jam resistance) LPI (low probability of intercept)
image watermarked image Spread Spectrum Approaches • Images [Cox et al. 1997] • Discrete cosine transform • Modifying the most important coefficients frequency domain
3D mesh basis functions watermarked mesh basis function Spread Spectrum Approaches • 3D meshes [Praun et al. 1999] • Multiresolution analysis
… … motion data motion signal Our Approach • Spread spectrum watermarking for motion Motion data = bundle of motion signals of position or orientation
Our Approach Problem: Difficult to obtain frequency information from the motion data due to complication caused by orientations Solution: Extracting frequency information from multiresolution representation
Multiresolution Representation • Representing at multiple resolutions • Hierarchy of successive smoother and coarser signals • Hierarchy of displacement maps
Reduction Reduction Reduction Expansion Expansion Expansion Decomposition Reduction : smoothing, followed by down-sampling Expansion : up-sampling, followed by smoothing • Both of them can be realized by spatial masking [Lee2000]
… … • Reconstruction … Representation and Reconstruction • Representation …
Motion Watermarking Based on multiresolution analysis • Watermark insertion • Watermark extraction • Analysis of similarity between inserted and extracted watermarks
coarse base signal original signal … Multiresolution Representation detail coefficients Watermark Insertion • Decomposing motion signal
watermark coefficient coarse base signal coarse base signal scaling parameter original signal … … the i-th largest coefficient altered coefficient detail coefficients detail coefficients Watermark Insertion • Perturbing the largest coefficients
coarse base signal original signal watermarked signal … detail coefficients Watermark Insertion • Reconstructing the motion signal
watermark signal watermarked motion + original motion Watermark Insertion • Perturbation of coefficient Embedding watermark into wide range
original signal original signal registered suspect signal suspect signal dynamic time warping resampling Watermark Extraction • Registering original and suspect motion • Using dynamic time warping [Bruderlin1995]
coarse base signal coarse base signal original signal suspect signal … … detail coefficients detail coefficients Watermark Extraction • Decomposing motion signals
coarse base signal coarse base signal comparing … … detail coefficients detail coefficients Watermark Extraction • Comparing watermarked coefficients
scaling parameter Watermark Extraction • Extracting suspect watermark • Obtaining from
Analysis of Similarity • Computing false-positive probability • False-positive probability (Pfp ): Probability of incorrectly asserting that the data is watermarked when it is not • Using Student’s t-test • From correlation
Data A Data B Data C Data D Experimental Results
Experimental Results • Original Motion and Watermarked Motion • Fly Spin Kick
Experimental Results • Original Motion and Watermarked Motion • Blown Back
Experimental Results • Results for various attacks • Adding noise attack on Fly Spin Kick
Experimental Results • Results for various attacks • Adding the second watermark on Fly Spin Kick
Experimental Results • Results for various attacks • Smoothing attack on Blown Back
Experimental Results • Results for various attacks • Time warping attack on Blown Back
Conclusion and Future Works • Watermarking schemes for motion data • Spread spectrum approach • Using multiresolution motion analysis • Robust to attacks • Future works • Consideration for other attacks • Blind detection • Watermark extraction from rendered images
Q/A : False-negative Probability • False-negative Probability Probability of failing to detect watermarked data • lesser important than false-positive probability • More difficult to analyze since it depends on the type and magnitude of attacks
random numbers original data hashed value owner’s key Q/A : Non-invertible Watermark • Generating non-invertible watermark randomly selected from • seeded by cryptographic hash function with (original data + owner’s key)
